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Expected value of information and decision making in HTA
Author(s) -
Eckermann Simon,
Willan Andrew R.
Publication year - 2007
Publication title -
health economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.55
H-Index - 109
eISSN - 1099-1050
pISSN - 1057-9230
DOI - 10.1002/hec.1161
Subject(s) - value of information , intervention (counseling) , actuarial science , value (mathematics) , cost–benefit analysis , optimal decision , medicine , risk analysis (engineering) , computer science , economics , decision tree , data mining , ecology , artificial intelligence , psychiatry , machine learning , biology
Decision makers within a jurisdiction facing evidence of positive but uncertain incremental net benefit of a new health care intervention have viable options where no further evidence is anticipated to: (1) adopt the new intervention without further evidence; (2) adopt the new intervention and undertake a trial; or (3) delay the decision and undertake a trial. Value of information methods have been shown previously to allow optimal design of clinical trials in comparing option (2) against option (1), by trading off the expected value and cost of sample information. However, this previous research has not considered the effect of cost of reversal on expected value of information in comparing these options. This paper demonstrates that, where a new intervention is adopted, the expected value of information is reduced under optimal decision making with costs of reversing decisions. Further, the paper shows that comparing expected net gain of optimally designed trials for option (2) vs (1) conditional on cost of reversal, and (3) vs (1) conditional on opportunity cost of delay allow systematic identification of an optimal decision strategy and trial design. Copyright © 2006 John Wiley & Sons, Ltd.